Timely and accurate syndromic surveillance depends on continuous data feeds from healthcare facilities. Typical outlier detection methodologies in syndromic surveillance compare predictions of counts for an interval to observed event counts, either to detect increases in volume associated with public health incidents or decreases in volume associated with compromised data transmission.

BioSense is a national program designed to improve the nation’s capabilities for conducting disease detection, monitoring, and real-time situational awareness. Currently, BioSense receives near real-time data from non-federal hospitals, as well as national daily batched data from the Departments of Defense and Veteran’s Affairs facilities.  These data are analyzed, visualized, and made simultaneously available to public health at local, state, and federal levels through the BioSense application.

Objective:

This paper examines the continued usefulness, through the 2005-06 influenza season, of a hospital admissions-based syndromic surveillance system as a supplement to laboratory and clinical influenza surveillance in preparation for pandemic influenza.

With the recent emphasis on public health preparedness, health departments are identifying new ways to prepare for emergencies. There has been a significant increase in the number of syndromic surveillance systems operating in recent years. These systems are based on real-time information from hospital emergency departments that is transmitted and analyzed electronically for the purpose of early detection of public health emergencies. Like other states, Rhode Island sought to enhance its traditional surveillance activities through the implementation of such a system.